Fuzzy Enhanced Control of an Underactuated Finger Using Tactile and Position Sensors
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Bibliographic record
Abstract
This paper proposes a control scheme dedicated to underactuated fingers with the intention of maximizing the capabilities of the latter using tactile and position information at a minimum cost. Tactile sensors are implemented on one prototype of underactuated finger and used to enhance the behaviour of the hand despite its limited number of control signals. First, tactile technology is briefly recalled and discussed. Second, the electronic design of the sensors' controller is presented. Third, a real-time control scheme is introduced, based on a fuzzy force control method. Finally, a slippage prevention technique is presented. Results are discussed based on experimental observations and indicate that the behaviour of underactuated fingers can be substantially enhanced with tactile information and a classic fuzzy control approach.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it